temporal_expression#

scdiffeq.plotting._temporal_expression.temporal_expression(adata_sim: AnnData, gene: str, groupby: str = 'final_state', groups: List[str] | None = None, use_key: str = 'X_gene_inv', time_key: str = 't', gene_ids_key: str = 'gene_ids', show_std: bool = True, std_alpha: float = 0.2, ax: Axes | None = None, figsize: tuple = (3, 2.5), cmap: Dict[str, str] | None = None, linewidth: float = 2.0, x_label: str = 't(d)', y_label: str = 'Log-norm. expression', title: str | None = None, show_legend: bool = True, legend_loc: str | tuple = 'best', grid: bool = True, grid_alpha: float = 0.3, save: bool = False, savename: str | None = None, save_format: str = 'svg', dpi: int = 300) → Axes[source]#

Plot gene expression over simulated time, grouped by fate.

Computes mean and standard deviation at each time step and plots as line (mean) with shaded fill-between region (±1 std).

Parameters:

  • adata_sim (AnnData) – Simulated data from sdq.tl.simulate(), with gene expression stored in obsm after calling sdq.tl.invert_scaled_gex().

  • gene (str) – Gene name to plot.

  • groupby (str, default="final_state") – Column in adata_sim.obs for grouping trajectories (e.g., cell fate).

  • groups (List[str], optional) – Specific groups to plot. If None, plots all groups. Use this to exclude certain groups (e.g., groups=["Mon.", "Neu."] to only plot those two fates).

  • use_key (str, default="X_gene_inv") – Key in adata_sim.obsm containing the gene expression matrix.

  • time_key (str, default="t") – Column in adata_sim.obs containing time values.

  • gene_ids_key (str, default="gene_ids") – Key in adata_sim.uns containing gene names array.

  • show_std (bool, default=True) – Whether to show standard deviation as shaded fill-between region.

  • std_alpha (float, default=0.2) – Transparency of the standard deviation shading.

  • ax (plt.Axes, optional) – Matplotlib axes to plot on. If None, creates new figure.

  • figsize (tuple, default=(3, 2.5)) – Figure size (width, height) in inches if creating new figure.

  • cmap (Dict[str, str], optional) – Mapping from group names to colors. If None, uses default colormap.

  • linewidth (float, default=2.0) – Width of the mean line.

  • x_label (str, default="t(d)") – Label for x-axis.

  • y_label (str, default="Log-norm. expression") – Label for y-axis.

  • title (str, optional) – Plot title. If None, uses gene name in italic.

  • show_legend (bool, default=True) – Whether to show legend.

  • legend_loc (str or tuple, default="best") – Legend location.

  • grid (bool, default=True) – Whether to show grid.

  • grid_alpha (float, default=0.3) – Transparency of grid lines.

  • save (bool, default=False) – Whether to save the figure.

  • savename (str, optional) – Filename for saving. If None, auto-generates from gene name.

  • save_format (str, default="svg") – Format for saving figure.

  • dpi (int, default=300) – Resolution for saving figure.

Returns:

The matplotlib axes object.

Return type:

plt.Axes

Examples

>>> import scdiffeq as sdq
>>> adata_sim = sdq.tl.simulate(adata, diffeq=model, idx=idx)
>>> sdq.tl.invert_scaled_gex(adata_sim, ...)
>>> sdq.tl.annotate_cell_fate(adata_sim, ...)
>>> sdq.pl.temporal_expression(
...     adata_sim,
...     gene="Spi1",
...     groupby="final_state",
...     cmap={"Mon.": "orange", "Neu.": "#4a7298"}
... )
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